Moving Target Tracking Based on Kalman Algorithm

Problems concerning moving target tracking are being proposed and applied widely currently along with the maturity of computer technology and the fast advancement of computer vision. As a very important area in computer vision, moving target tracking is widely used in real life, for example, interactivity between human and computer, and so on. In this paper, Kalman filter, as a highly efficient recursive filter, is the common video method employed to track moving object in video. The moving state of moving object can be estimated in accordance with the location of the moving target. The tracking video is decomposed into frames in the initialization period and every frame is made up of a piece of picture; then, the targets in each frame are identified by means of color recognition; next, position the moving target, identify the center coordinates; at last, the coordinate of the previous and current frames is inputted and the location of the moving target in the present frame is estimated by Kalman filter.